Method of obtaining mask frame data, computing device, and readable storage medium

Plain English Translation

The invention relates to image processing, specifically to methods for identifying and analyzing regions of interest within a frame, such as in video or image analysis applications. The problem addressed is the need for accurate and efficient segmentation of a main area within a frame, which is crucial for tasks like object detection, scene understanding, or automated content analysis. The method involves using an image segmentation algorithm to isolate the main area of the frame. Specifically, an instance segmentation model is employed to distinguish the main area from other regions. Instance segmentation not only classifies pixels but also differentiates between individual objects or regions within the frame, providing precise boundaries for the main area. This approach improves accuracy over traditional segmentation techniques by leveraging deep learning models that can handle complex scenes with multiple overlapping objects. The instance segmentation model is trained to recognize and segment the main area based on features such as shape, texture, or contextual information. The output is a segmented frame where the main area is clearly delineated, enabling further processing like object tracking, anomaly detection, or content-based retrieval. This method is particularly useful in applications requiring high precision, such as medical imaging, autonomous driving, or surveillance systems. The use of instance segmentation ensures that the main area is accurately identified even in cluttered or dynamic environments.